Sensory Analysis

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Urska Vrhovsek - One of the best experts on this subject based on the ideXlab platform.

  • Untangling the wine metabolome by combining untargeted SPME–GCxGC-TOF-MS and Sensory Analysis to profile Sauvignon blanc co-fermented with seven different yeasts
    Metabolomics, 2016
    Co-Authors: Margaret E. Beckner Whitener, Jan Stanstrup, Valeria Panzeri, Silvia Carlin, Benoit Divol, Maret Toit, Urska Vrhovsek
    Abstract:

    Saccharomyces cerevisiae ( SC ) is the main driver of alcoholic fermentation, however for aroma and flavor formation in wine, non- Saccharomyces species can have a powerful effect. This study aimed to compare untargeted volatile compound profiles from SPME–GCxGC-TOF-MS and Sensory Analysis data of Sauvignon blanc wine inoculated with six different non- Saccharomyces yeasts followed by SC . Torulaspora delbrueckii ( TD ), Lachancea thermotolerans ( LT ), Pichia kluyveri ( PK ) and Metschnikowia pulcherrima ( MP ) where commercial starter strains, while Candida zemplinina ( CZ ) and Kazachstania aerobia ( KA ), were isolated from wine grape environments. Each wine showed a distinct profile both sensorially and chemically. SC and CZ wines were the most distinct in both of these cases. SC wine had guava, grapefruit, banana, and pineapple aromas while CZ wine was driven by fermented apple, dried peach/apricot, and stewed fruit as well as sour flavor. Chemically over 300 unique features were identified as significantly different across the fermentations. SC wine had the highest number of esters in the highest relative concentration but all the yeasts had distinct ester profiles. CZ wine displayed the highest number of terpenes in high concentration but also produced a large amount of acetic acid. KA wine was high in ethyl acetate. TD wine had fewer esters but three distinctly higher thiol compounds. LT wine showed a relatively high number of increased acetate esters and certain terpenes. PK wine had some off odor compounds while the MP wine had high levels of methyl butyl-, methyl propyl-, and phenethyl esters. Overall, this study gives a more detailed profile of these yeasts contribution to Sauvignon blanc wine than previously reported.

  • untangling the wine metabolome by combining untargeted spme gcxgc tof ms and Sensory Analysis to profile sauvignon blanc co fermented with seven different yeasts
    Metabolomics, 2016
    Co-Authors: M E B Whitener, Jan Stanstrup, Valeria Panzeri, Silvia Carlin, Benoit Divol, Maret Toit, Urska Vrhovsek
    Abstract:

    Saccharomyces cerevisiae (SC) is the main driver of alcoholic fermentation, however for aroma and flavor formation in wine, non-Saccharomyces species can have a powerful effect. This study aimed to compare untargeted volatile compound profiles from SPME–GCxGC-TOF-MS and Sensory Analysis data of Sauvignon blanc wine inoculated with six different non-Saccharomyces yeasts followed by SC. Torulaspora delbrueckii (TD), Lachancea thermotolerans (LT), Pichia kluyveri (PK) and Metschnikowia pulcherrima (MP) where commercial starter strains, while Candida zemplinina (CZ) and Kazachstania aerobia (KA), were isolated from wine grape environments. Each wine showed a distinct profile both sensorially and chemically. SC and CZ wines were the most distinct in both of these cases. SC wine had guava, grapefruit, banana, and pineapple aromas while CZ wine was driven by fermented apple, dried peach/apricot, and stewed fruit as well as sour flavor. Chemically over 300 unique features were identified as significantly different across the fermentations. SC wine had the highest number of esters in the highest relative concentration but all the yeasts had distinct ester profiles. CZ wine displayed the highest number of terpenes in high concentration but also produced a large amount of acetic acid. KA wine was high in ethyl acetate. TD wine had fewer esters but three distinctly higher thiol compounds. LT wine showed a relatively high number of increased acetate esters and certain terpenes. PK wine had some off odor compounds while the MP wine had high levels of methyl butyl-, methyl propyl-, and phenethyl esters. Overall, this study gives a more detailed profile of these yeasts contribution to Sauvignon blanc wine than previously reported.

Zuobing Xiao - One of the best experts on this subject based on the ideXlab platform.

  • evaluation of the synergism among volatile compounds in oolong tea infusion by odour threshold with Sensory Analysis and e nose
    Food Chemistry, 2017
    Co-Authors: Jiancai Zhu, Lingying Wang, Feng Chen, Yunwei Niu, Zuobing Xiao
    Abstract:

    Twenty-four kinds of representative aroma compounds in Oolong tea were selected to evaluate the interactions by the variation in the threshold values of these compounds before, and after, they were mixed. Result demonstrated that the ratios of the referenced threshold values of heptanal, β-damascenone, and methional to their determined thresholds were larger, namely, 5, 3.85, and 2.5, respectively. On the other hand, the mixed compounds with similar structure and aroma mainly presented a synergistic effect and additive action. Moreover, a masking effect was found among compounds with different structures. (E)-2-hexenal was added to tea infusion at a concentration below its threshold level to investigate whether, or not, the sub-threshold compounds affected the overall odour sensation of Oolong tea by Sensory Analysis and electronic nose (E-nose). The result indicated that the aroma of the tea infusion with added (E)-2-hexenal had changed before, and after, they were mixed.

  • evaluation of the synergism among volatile compounds in oolong tea infusion by odour threshold with Sensory Analysis and e nose
    Food Chemistry, 2017
    Co-Authors: Lingying Wang, Feng Chen, Zuobing Xiao
    Abstract:

    Abstract Twenty-four kinds of representative aroma compounds in Oolong tea were selected to evaluate the interactions by the variation in the threshold values of these compounds before, and after, they were mixed. Result demonstrated that the ratios of the referenced threshold values of heptanal, β-damascenone, and methional to their determined thresholds were larger, namely, 5, 3.85, and 2.5, respectively. On the other hand, the mixed compounds with similar structure and aroma mainly presented a synergistic effect and additive action. Moreover, a masking effect was found among compounds with different structures. (E)-2-hexenal was added to tea infusion at a concentration below its threshold level to investigate whether, or not, the sub-threshold compounds affected the overall odour sensation of Oolong tea by Sensory Analysis and electronic nose (E-nose). The result indicated that the aroma of the tea infusion with added (E)-2-hexenal had changed before, and after, they were mixed.

  • contribution of beef base to aroma characteristics of beeflike process flavour assessed by descriptive Sensory Analysis and gas chromatography olfactometry and partial least squares regression
    Journal of Chromatography A, 2010
    Co-Authors: Shiqing Song, Xiaoming Zhang, Khizar Hayat, Meigui Huang, Eric Karangwa, Fenglin Gu, Zuobing Xiao
    Abstract:

    Abstract Descriptive Sensory Analysis and gas chromatography–mass spectrometry (GC–MS) Analysis were conducted to investigate changes in aroma characteristics of beeflike process flavours (BPFs) prepared from enzymatically hydrolyzed beef (beef base) of different DH (degree of hydrolysis) with other ingredients. Five attributes (beefy, meaty, simulate, mouthful and roasted) were selected to assess BPFs. The results of descriptive Sensory Analysis confirmed that BPF2 from beef base of moderate DH 29.13% was strongest in beefy, meaty and simulate characteristics; BPF4 and BPF5 from beef base of higher DH (40.43% and 44.22%, respectively) were superior in mouthful and roasted attributes respectively; while BPF0 without beef base gave weaker odour for all attributes. Twenty six compounds from GC–MS were selected as specific compounds to represent beef odour based on their odour-active properties assessed by a detection frequency method of GC–O and correlation of their contents with Sensory attributes intensity. Correlation Analysis of molecular weight (MW) of peptides, odour-active compounds and Sensory attributes through partial least squares regression (PLSR) further explained that beef base with DH of 29.13% was a desirable precursor for imparting aroma characteristics of beeflike process flavour.

Feng Chen - One of the best experts on this subject based on the ideXlab platform.

  • evaluation of the synergism among volatile compounds in oolong tea infusion by odour threshold with Sensory Analysis and e nose
    Food Chemistry, 2017
    Co-Authors: Lingying Wang, Feng Chen, Zuobing Xiao
    Abstract:

    Abstract Twenty-four kinds of representative aroma compounds in Oolong tea were selected to evaluate the interactions by the variation in the threshold values of these compounds before, and after, they were mixed. Result demonstrated that the ratios of the referenced threshold values of heptanal, β-damascenone, and methional to their determined thresholds were larger, namely, 5, 3.85, and 2.5, respectively. On the other hand, the mixed compounds with similar structure and aroma mainly presented a synergistic effect and additive action. Moreover, a masking effect was found among compounds with different structures. (E)-2-hexenal was added to tea infusion at a concentration below its threshold level to investigate whether, or not, the sub-threshold compounds affected the overall odour sensation of Oolong tea by Sensory Analysis and electronic nose (E-nose). The result indicated that the aroma of the tea infusion with added (E)-2-hexenal had changed before, and after, they were mixed.

  • evaluation of the synergism among volatile compounds in oolong tea infusion by odour threshold with Sensory Analysis and e nose
    Food Chemistry, 2017
    Co-Authors: Jiancai Zhu, Lingying Wang, Feng Chen, Yunwei Niu, Zuobing Xiao
    Abstract:

    Twenty-four kinds of representative aroma compounds in Oolong tea were selected to evaluate the interactions by the variation in the threshold values of these compounds before, and after, they were mixed. Result demonstrated that the ratios of the referenced threshold values of heptanal, β-damascenone, and methional to their determined thresholds were larger, namely, 5, 3.85, and 2.5, respectively. On the other hand, the mixed compounds with similar structure and aroma mainly presented a synergistic effect and additive action. Moreover, a masking effect was found among compounds with different structures. (E)-2-hexenal was added to tea infusion at a concentration below its threshold level to investigate whether, or not, the sub-threshold compounds affected the overall odour sensation of Oolong tea by Sensory Analysis and electronic nose (E-nose). The result indicated that the aroma of the tea infusion with added (E)-2-hexenal had changed before, and after, they were mixed.

Jan Stanstrup - One of the best experts on this subject based on the ideXlab platform.

  • Untangling the wine metabolome by combining untargeted SPME–GCxGC-TOF-MS and Sensory Analysis to profile Sauvignon blanc co-fermented with seven different yeasts
    Metabolomics, 2016
    Co-Authors: Margaret E. Beckner Whitener, Jan Stanstrup, Valeria Panzeri, Silvia Carlin, Benoit Divol, Maret Toit, Urska Vrhovsek
    Abstract:

    Saccharomyces cerevisiae ( SC ) is the main driver of alcoholic fermentation, however for aroma and flavor formation in wine, non- Saccharomyces species can have a powerful effect. This study aimed to compare untargeted volatile compound profiles from SPME–GCxGC-TOF-MS and Sensory Analysis data of Sauvignon blanc wine inoculated with six different non- Saccharomyces yeasts followed by SC . Torulaspora delbrueckii ( TD ), Lachancea thermotolerans ( LT ), Pichia kluyveri ( PK ) and Metschnikowia pulcherrima ( MP ) where commercial starter strains, while Candida zemplinina ( CZ ) and Kazachstania aerobia ( KA ), were isolated from wine grape environments. Each wine showed a distinct profile both sensorially and chemically. SC and CZ wines were the most distinct in both of these cases. SC wine had guava, grapefruit, banana, and pineapple aromas while CZ wine was driven by fermented apple, dried peach/apricot, and stewed fruit as well as sour flavor. Chemically over 300 unique features were identified as significantly different across the fermentations. SC wine had the highest number of esters in the highest relative concentration but all the yeasts had distinct ester profiles. CZ wine displayed the highest number of terpenes in high concentration but also produced a large amount of acetic acid. KA wine was high in ethyl acetate. TD wine had fewer esters but three distinctly higher thiol compounds. LT wine showed a relatively high number of increased acetate esters and certain terpenes. PK wine had some off odor compounds while the MP wine had high levels of methyl butyl-, methyl propyl-, and phenethyl esters. Overall, this study gives a more detailed profile of these yeasts contribution to Sauvignon blanc wine than previously reported.

  • untangling the wine metabolome by combining untargeted spme gcxgc tof ms and Sensory Analysis to profile sauvignon blanc co fermented with seven different yeasts
    Metabolomics, 2016
    Co-Authors: M E B Whitener, Jan Stanstrup, Valeria Panzeri, Silvia Carlin, Benoit Divol, Maret Toit, Urska Vrhovsek
    Abstract:

    Saccharomyces cerevisiae (SC) is the main driver of alcoholic fermentation, however for aroma and flavor formation in wine, non-Saccharomyces species can have a powerful effect. This study aimed to compare untargeted volatile compound profiles from SPME–GCxGC-TOF-MS and Sensory Analysis data of Sauvignon blanc wine inoculated with six different non-Saccharomyces yeasts followed by SC. Torulaspora delbrueckii (TD), Lachancea thermotolerans (LT), Pichia kluyveri (PK) and Metschnikowia pulcherrima (MP) where commercial starter strains, while Candida zemplinina (CZ) and Kazachstania aerobia (KA), were isolated from wine grape environments. Each wine showed a distinct profile both sensorially and chemically. SC and CZ wines were the most distinct in both of these cases. SC wine had guava, grapefruit, banana, and pineapple aromas while CZ wine was driven by fermented apple, dried peach/apricot, and stewed fruit as well as sour flavor. Chemically over 300 unique features were identified as significantly different across the fermentations. SC wine had the highest number of esters in the highest relative concentration but all the yeasts had distinct ester profiles. CZ wine displayed the highest number of terpenes in high concentration but also produced a large amount of acetic acid. KA wine was high in ethyl acetate. TD wine had fewer esters but three distinctly higher thiol compounds. LT wine showed a relatively high number of increased acetate esters and certain terpenes. PK wine had some off odor compounds while the MP wine had high levels of methyl butyl-, methyl propyl-, and phenethyl esters. Overall, this study gives a more detailed profile of these yeasts contribution to Sauvignon blanc wine than previously reported.

Valeria Panzeri - One of the best experts on this subject based on the ideXlab platform.

  • Untangling the wine metabolome by combining untargeted SPME–GCxGC-TOF-MS and Sensory Analysis to profile Sauvignon blanc co-fermented with seven different yeasts
    Metabolomics, 2016
    Co-Authors: Margaret E. Beckner Whitener, Jan Stanstrup, Valeria Panzeri, Silvia Carlin, Benoit Divol, Maret Toit, Urska Vrhovsek
    Abstract:

    Saccharomyces cerevisiae ( SC ) is the main driver of alcoholic fermentation, however for aroma and flavor formation in wine, non- Saccharomyces species can have a powerful effect. This study aimed to compare untargeted volatile compound profiles from SPME–GCxGC-TOF-MS and Sensory Analysis data of Sauvignon blanc wine inoculated with six different non- Saccharomyces yeasts followed by SC . Torulaspora delbrueckii ( TD ), Lachancea thermotolerans ( LT ), Pichia kluyveri ( PK ) and Metschnikowia pulcherrima ( MP ) where commercial starter strains, while Candida zemplinina ( CZ ) and Kazachstania aerobia ( KA ), were isolated from wine grape environments. Each wine showed a distinct profile both sensorially and chemically. SC and CZ wines were the most distinct in both of these cases. SC wine had guava, grapefruit, banana, and pineapple aromas while CZ wine was driven by fermented apple, dried peach/apricot, and stewed fruit as well as sour flavor. Chemically over 300 unique features were identified as significantly different across the fermentations. SC wine had the highest number of esters in the highest relative concentration but all the yeasts had distinct ester profiles. CZ wine displayed the highest number of terpenes in high concentration but also produced a large amount of acetic acid. KA wine was high in ethyl acetate. TD wine had fewer esters but three distinctly higher thiol compounds. LT wine showed a relatively high number of increased acetate esters and certain terpenes. PK wine had some off odor compounds while the MP wine had high levels of methyl butyl-, methyl propyl-, and phenethyl esters. Overall, this study gives a more detailed profile of these yeasts contribution to Sauvignon blanc wine than previously reported.

  • untangling the wine metabolome by combining untargeted spme gcxgc tof ms and Sensory Analysis to profile sauvignon blanc co fermented with seven different yeasts
    Metabolomics, 2016
    Co-Authors: M E B Whitener, Jan Stanstrup, Valeria Panzeri, Silvia Carlin, Benoit Divol, Maret Toit, Urska Vrhovsek
    Abstract:

    Saccharomyces cerevisiae (SC) is the main driver of alcoholic fermentation, however for aroma and flavor formation in wine, non-Saccharomyces species can have a powerful effect. This study aimed to compare untargeted volatile compound profiles from SPME–GCxGC-TOF-MS and Sensory Analysis data of Sauvignon blanc wine inoculated with six different non-Saccharomyces yeasts followed by SC. Torulaspora delbrueckii (TD), Lachancea thermotolerans (LT), Pichia kluyveri (PK) and Metschnikowia pulcherrima (MP) where commercial starter strains, while Candida zemplinina (CZ) and Kazachstania aerobia (KA), were isolated from wine grape environments. Each wine showed a distinct profile both sensorially and chemically. SC and CZ wines were the most distinct in both of these cases. SC wine had guava, grapefruit, banana, and pineapple aromas while CZ wine was driven by fermented apple, dried peach/apricot, and stewed fruit as well as sour flavor. Chemically over 300 unique features were identified as significantly different across the fermentations. SC wine had the highest number of esters in the highest relative concentration but all the yeasts had distinct ester profiles. CZ wine displayed the highest number of terpenes in high concentration but also produced a large amount of acetic acid. KA wine was high in ethyl acetate. TD wine had fewer esters but three distinctly higher thiol compounds. LT wine showed a relatively high number of increased acetate esters and certain terpenes. PK wine had some off odor compounds while the MP wine had high levels of methyl butyl-, methyl propyl-, and phenethyl esters. Overall, this study gives a more detailed profile of these yeasts contribution to Sauvignon blanc wine than previously reported.